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What is Agentic Coding?

Agentic coding tools like Cursor, Cline, and Codex CLI work differently from chat interfaces. Instead of answering questions, they read your codebase, plan changes, apply patches, run tests, inspect errors, and iterate until the work is done - often executing 50 to 200+ turns per task. This makes inference speed critical: every extra 100ms per turn compounds across hundreds of iterations, turning a 10-minute task into an hour-long wait.

MiniMax M2.7 Ultraspeed on Infercom delivers 400+ tokens per second while matching frontier model performance on coding benchmarks. Whether you're using it as a full replacement or splitting planning and execution across providers, fast inference means faster iteration cycles, lower costs, and more responsive coding workflows.

428 tok/s

Measured on our production API in Munich. Less waiting, more coding.

Output Throughput, p50, 10K input / 1K output, single request. Last measured: July 2026.

€0.60 / €2.40

Per 1M tokens (input/output), excl. VAT. Pay only for the tokens your agents use.

EU Sovereign

Data processed in Germany. No persistent storage and no training on your data.

Scale Without Surprises

Transparent pay-as-you-go pricing. Know exactly what you'll pay before you start.

Two Ways to Run Agentic Coding on Infercom

Replace your frontier model entirely, or keep it for planning and offload execution

MiniMax M2.7 Ultraspeed matches frontier models on coding benchmarks at a fraction of the cost. You can use it for everything - or split the load between planning and execution.

Full Replacement

Use MiniMax M2.7 Ultraspeed for everything

  • Simplest setup - one model, one provider
  • 56% SWE-Pro - matches frontier performance
  • 400+ tokens/sec on EU infrastructure

Best for: Cost-conscious teams, high-volume workloads

Planner/Executor Split

Keep your frontier model for planning

  • Planning: Claude, GPT, or Gemini (5-15 turns)
  • Execution: MiniMax M2.7 Ultraspeed on Infercom (50-200+ turns)
  • Best of both - frontier reasoning + fast execution

Best for: Teams already invested in frontier models

Both options run on EU sovereign infrastructure with full GDPR compliance. Tools with native support: Codex CLI, Cline, OpenCode, Cursor, and more.

See Configuration Guides

Why Fast Inference Matters for Coding Agents

Agentic workflows are iteration-heavy. Speed directly impacts productivity and cost.

Execution Dominates

Coding agents spend 80-95% of their turns on execution - file reads, edits, test runs, retries. A 4x speedup on execution means 3-4x faster overall task completion.

Tokens Add Up Fast

Every call in an agentic loop resends the growing conversation, so a single coding task can send hundreds of thousands of input tokens. That makes the price per token the number to watch: €0.60 input and €2.40 output per million tokens on Infercom, excl. VAT.

Faster Feedback Loops

When each iteration returns in seconds instead of minutes, you can review, adjust, and re-run more frequently. Speed enables tighter human-in-the-loop workflows.

Built for Agentic Workflows

MiniMax M2.7 Ultraspeed delivers frontier-level coding performance with native multi-agent capabilities

56%

SWE-Pro

Professional software engineering

76.5%

SWE Multilingual

Cross-language coding

57%

Terminal Bench 2

CLI and system tasks

66.6%

MLE Bench Lite

ML engineering competitions

MiniMax M2.7 Ultraspeed achieved a 30% performance improvement through autonomous iteration cycles - analyzing, planning, modifying, and evaluating code without human intervention.
SambaNova Blog

Works With Your Favorite Tools

Drop-in replacement via OpenAI-compatible API. Switch in minutes.

These tools are developed by their respective creators. Infercom is not affiliated with or endorsed by these projects.

View All Integration Guides

See It In Action

Real agentic coding with MiniMax M2.7 Ultraspeed on EU infrastructure

OpenCode with MiniMax M2.7 Ultraspeed on Infercom - reasoning, tool calling, and file operations at 400+ tokens/sec

Developers Are Moving to Open-Weight Models

Three independent signals from 2025 and 2026.

1/3

of tokens on open-weight models

By late 2025, open-weight models handled about a third of all tokens on OpenRouter. Coding grew from 11% to more than half of all tokens in the same year.

OpenRouter and a16z, State of AI (Jan 2026)

60-70%

AT&T's target for open models

AT&T already sends 40% of employee AI queries to open models. Routing tasks to cheaper models cut its coding costs by up to 56%, with 2% lower quality.

The Information, via PYMNTS (Aug 2026)

75.8%

SWE-bench Verified, open-weight

MiniMax M2.5, the predecessor of the model we serve, resolved 75.8% of tasks - one point behind the best closed model (76.8%).

SWE-bench leaderboard, bash-only (Feb 2026)

Your code, your prompts, your data - processed entirely on EU infrastructure. No US CLOUD Act exposure.

Frequently Asked Questions

What is agentic coding?

Agentic coding uses AI models to autonomously perform software development tasks - reading code, making changes, running tests, and iterating until the work is complete. Unlike chat-based coding assistants that answer questions, agentic tools like Cursor, Cline, Aider, and Codex CLI execute multi-step workflows with minimal human intervention.

How does Infercom compare to using Claude or GPT directly?

MiniMax M2.7 Ultraspeed on Infercom reaches 56% on SWE-Pro at a fraction of frontier per-token prices: €0.60 input and €2.40 output per million tokens (excl. VAT). For agentic coding, where a task can run 50-200+ turns and resend its context on every turn, the price per token decides what a task costs. You also get EU data residency and 400+ tokens per second.

Can I use Infercom with Cursor, Cline, or other coding tools?

Yes. Infercom provides both OpenAI-compatible and Anthropic-compatible APIs, so any tool that supports custom API endpoints works out of the box. We have integration guides for Cursor, Cline, Codex CLI, Aider, OpenCode, Continue, Windsurf, Claude Code, and more. Setup takes 2-5 minutes.

See API compatibility documentation

What is the planner/executor pattern?

The planner/executor pattern splits agentic workloads between two models: a frontier model (Claude, GPT, Gemini) handles planning - understanding the codebase, assessing risks, deciding what to build - while a fast model (MiniMax M2.7 Ultraspeed on Infercom) handles execution - applying changes, running tests, fixing errors. This gives you frontier-quality reasoning where it matters most, with fast, cost-effective execution for the bulk of the work.

Is my code data safe on Infercom?

Yes. Infercom processes all data on EU infrastructure in Germany. We're ISO 27001 certified, fully GDPR compliant, and operate with no persistent storage - your code is never stored persistently or used for training. There's no US CLOUD Act exposure.

What models are available for agentic coding?

Our flagship model for agentic coding is MiniMax M2.7 Ultraspeed, which offers 192K context, built-in self-critique, native agent teams, and 400+ tokens/second throughput. We also offer gpt-oss-120b and other models. Check our model catalog for current availability.

How do I get started with agentic coding on Infercom?

Sign up at cloud.infercom.ai and generate an API key, configure your coding tool to use api.infercom.ai as the base URL, and start coding. Most users are up and running in under 5 minutes.

See our agentic coding documentation for step-by-step setup guides

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